• DocumentCode
    768022
  • Title

    Temperature regulation with neural networks and alternative control schemes

  • Author

    Khalid, Marzuki ; Omatu, Sigeru ; Yusof, Rubiyah

  • Author_Institution
    Dept. of Inf. Sci. & Intelligent Syst., Tokushima Univ., Japan
  • Volume
    6
  • Issue
    3
  • fYear
    1995
  • fDate
    5/1/1995 12:00:00 AM
  • Firstpage
    572
  • Lastpage
    582
  • Abstract
    In this article, we compare the neuro-control algorithm to three other control algorithms: fuzzy logic control, generalized predictive control, and proportional-plus-integral control. Each of these four algorithms is implemented on a water bath temperature control system. The four systems are compared through experimental studies under identical conditions with respect to set-point regulation, the effect of unknown load disturbances, large parameter variation, and variable deadtime in the system. It is found that the neurocontrol system compares well with the other three control systems and offers encouraging advantages. From the results of the experimental studies, however, the best characteristics of each of these different classes of control systems may be combined for realizing a more efficient and intelligent control scheme
  • Keywords
    fuzzy control; intelligent control; neurocontrollers; predictive control; temperature control; deadtime; intelligent control; load disturbances; neural networks; neurocontrol system; set-point regulation; water bath temperature control; Adaptive control; Artificial neural networks; Automatic control; Control systems; Fuzzy logic; Fuzzy systems; Neural networks; Programmable control; Proportional control; Temperature control;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.377964
  • Filename
    377964